An important problem in large-scale information organization and processing is the generation of a much smaller document that best summarizes an original digital document. For example, a movie clip may provide a good preview of the movie. A book review describes a book in a short and concise fashion. An abstract of a paper provides the main results of the paper without giving out the details. A biography tells the life story of a person without recording every single events of his/her life. The summarization as mentioned above are often carefully produced from the original document manually. However, in the era where a large volume of documents are made publicly available on mediums such as the Internet, the problem of automatic summarization has become increasingly important.
There are vast differences in techniques for summarizing documents of different types and content. For example, sampling and coarsening can be applied to digital images. One approach to generate a smaller but similar image from an original digital image is to keep every kth pixel in the image, and hence reduce an n by n image to an n/k by n/k image. Some smoothing operations can be applied to the smaller image to make the coarsened image more visually pleasing. Another approach is to apply an image compression technique, such as JPAG and MTAG, where the coefficients of less significant basis components are eliminated.
In contrast, text-document summarization is much harder to automate. A compressed text file is often unreadable. Various heuristics techniques have been developed. For example, Microsoft Word software examines frequently-used terms in a document and picks sentences that may be close to the main theme, however, the summarization so produced is not quite appealing.
Although numerous compression techniques exist for compressing audio data, these techniques, as well as the summarization techniques described above for graphic and/or text information, are not applicable to the summarization of musical compositions. Because of the highly sophisticated structure and sequence of a musical composition and the aspects of the compositions which are recognizable to the listener, the task of efficiently summarizing a musical composition presents a number of difficult challenges which have yet to be addressed in the prior art. Accordingly, a need exists for a way in which musical compositions in a variety of formats and/or styles may be summarized to create a brief summary of the common theme of the composition so as to be readily recognized by a listener.
A further need exists for a method and technique in which the structure and aspects of a musical composition may be broken down into the primitive components of the musical composition and repetitive patterns detected and a summarization generated from the patterns.